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Record W4313887583 · doi:10.21203/rs.3.rs-2394919/v1

Synergistic inter-clonal cooperation involving crosstalk, co-option and co-dependency can enhance the invasiveness of genetically distant cancer clones

2023· preprint· en· W4313887583 on OpenAlexafffund
Caroline S. Carneiro, Jorian D. Hapeman, Aurora M. Nedelcu

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsUniversity of New Brunswick
FundersChina Scholarship CouncilNew Brunswick Innovation Foundation
KeywordsBiologyCrosstalkPhenotypeAutocrine signallingMetastasisCancer cellGenetic heterogeneityParacrine signallingCancerCancer researchclone (Java method)Somatic evolution in cancerGeneticsCell cultureGeneReceptor

Abstract

fetched live from OpenAlex

Abstract Background Despite intensive research, cancer remains a major health problem. The difficulties in treating cancer are due to the complex nature of this disease, including high levels of heterogeneity within tumours. Intra-tumour heterogeneity creates the conditions for inter-clonal competition and selection, which should result in selective sweeps and a reduction in levels of heterogeneity. However, in addition to competing, cancer clones could also cooperate with each other, and the positive effects of these interactions on the fitness of clones can actually contribute to maintaining the heterogeneity of tumours. Consequently, understanding the evolutionary mechanisms and pathways involved in such behaviours is of great significance for cancer treatment. This is particularly relevant for metastasis, which is the most lethal phase during cancer progression. To explore if and how genetically distant clones can cooperate during invasion, this study used three genetically distant cancer cell lines with different metastatic potentials. Results We found that (i) the conditioned media from the invasive lines increased the migration and invasion potential of the poorly metastatic line, and (ii) this inter-clonal interaction involved the TGF-β1 signalling pathway. Furthermore, when a highly and poorly metastatic lines were co-cultured, the invasive potential of both lines was enhanced, and this outcome was dependent on the co-option of the less aggressive clone into expressing a malignant phenotype. Based on our findings, we propose a two-tier model whereby highly metastatic clones can co-opt (through autocrine-paracrine crosstalk) weakly metastatic clones into expressing an invasive phenotype, which in turn augments the invasion ability of the former (i.e., a “help me help you” strategy). Conclusions We suggest that such synergistic cooperative interactions can easily emerge via crosstalk involving metastatic clones able to constitutively secrete molecules that induce and maintain their own malignant state (producer-responder clones) and clones that have the ability to respond to those signals (responder clones) and express a synergistic metastatic behaviour, regardless of the degree of overall genetic/genealogical relatedness. Taking into account the lack of therapies that directly affect the metastatic process, interfering with such cooperative behaviours that tumour cells engage in during the early steps in the metastatic cascade could provide additional strategies to increase patient survival.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.426
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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